RallyIQ

WTA · Right-handed · 78 charted matches · 2016–2026

Naomi Osaka

Archetype: First-strike aggressor · Short-point player

Against an average opponent

Serve points won 62.8% ±2.4 raw 61.3% · tour 56.3% · 5,343 points
Return points won 44.2% ±2.5 raw 41.3% · tour 43.7% · 5,350 points

Serve and return points won, refitted against every opponent at once so a record built on weak or strong opposition is put on the same scale. Career, all surfaces, with a 90% margin. Raw is the plain share of points won.

Value per 100 shots

Direction choice +0.15 ±0.06 better than 81% of WTA · raw +0.14
Shot selection +0.22 ±0.05 better than 70% of WTA · raw +0.21
Execution −0.20 ±0.34 better than 48% of WTA · raw −0.30
Tactical adaptability +0.16 first serves toward what's working, set to set · 75 matches
Adaptation speed +0.09 same, every two to three service games · per 100 first serves
Points left on the table 2.33 per 100 shots vs best direction · lower than 84% of WTA

Points gained per 100 shots compared with an average tour player in the same position, adjusted for the strength of the opponents faced, with a 90% margin (shots clustered by match). Raw is before the opponent adjustment. Built on 24,552 shots.

Shot expected value

The share of points Naomi Osaka goes on to win after each option in the positions they face most often, shrunk toward tour average when the sample is small. Showing the 8 most-used options; teal marks the best one with at least 30 shots.

Rally, shots 5–8: drive to your middle

position worth 50% to the average player · 1,432 shots

OptionUsedWin %Tour
FH crosscourt 26% 56.5%±4.1 52.7%
BH crosscourt 17% 50.1%±5.1 50.9%
FH down the line 17% 51.9%±5.1 52.2%
FH through the middle 15% 46.0%±5.3 45.8%
BH through the middle 13% 52.3%±5.8 46.2%
BH down the line 12% 50.0%±5.9 50.0%

Rally, shots 5–8: drive to your backhand side

position worth 45% to the average player · 1,225 shots

OptionUsedWin %Tour
BH crosscourt 52% 49.2%±3.2 47.6%
BH through the middle 24% 39.7%±4.6 43.3%
BH down the line 19% 44.7%±5.2 46.8%
BH slice through the middle 2% 30.8%±11.3 34.4%
BH slice crosscourt 1% 39.0%±14.4 40.4%
BH lob through the middle 1% 30.4%±13.6 27.1%
FH inside-out 1% 55.0%±14.9 52.5%

Rally, shots 5–8: drive to your forehand side

position worth 43% to the average player · 1,058 shots

OptionUsedWin %Tour
FH crosscourt 52% 48.7%±3.4 46.7%
FH through the middle 21% 45.8%±5.3 41.3%
FH down the line 17% 50.2%±5.8 44.9%
FH slice through the middle 5% 18.7%±7.5 29.2%
FH slice crosscourt 2% 30.2%±11.8 31.9%
FH slice down the line 1% 22.5%±11.6 24.3%

Return +1: drive to your middle

position worth 50% to the average player · 864 shots

OptionUsedWin %Tour
FH crosscourt 20% 57.6%±5.9 52.3%
FH down the line 19% 54.2%±6.1 53.0%
BH crosscourt 18% 45.0%±6.2 50.8%
BH through the middle 15% 47.2%±6.6 46.2%
FH through the middle 15% 45.3%±6.6 46.5%
BH down the line 12% 47.3%±7.3 50.6%

Serve under pressure

Pressure predictability index +5 How much less varied Naomi Osaka's first-serve direction gets on break points. Positive means easier to read. Based on 476 break-point first serves.

Deuce court

1st serveUsageBreak ptWon when in
Wide 44% 50% 75% / 66%
Body 13% 13% 62% / 57%
T 43% 37% 75% / 68%

2,663 normal · 123 break-point 1st serves

Ad court

1st serveUsageBreak ptWon when in
Wide 40% 34% 74% / 66%
Body 12% 9% 60% / 56%
T 48% 57% ▲ 70% / 64%

2,184 normal · 353 break-point 1st serves

Is the serve mix in equilibrium?

Game theory says a well-mixed server wins equally often with every direction they use. If one direction wins more, it's underused and points are being left behind. This is the minimax test Walker and Wooders ran on Wimbledon finals, applied to every charted first serve. Win rates include faults. "Optimal" allows for returners reading a habit. A direction loses 0.19 points per 100 serves for every 10 points of habitual usage, measured from WTA servers whose mix drifted between matches. Shifts stay within the range servers' habits actually vary, the only range that response was measured over.

Deuce court

1st serveUsagePoints wonOptimal
Wide44% 63.1%±2.2 n=1,230 59% ▲
Body13% 58.8%±4.1 n=355 0% ▼
T43% 62.5%±2.3 n=1,201 41% ▼

Consistent with an optimal mix (p = 0.26).
Optimal mix: +0.7 per 100 first serves.

Ad court

1st serveUsagePoints wonOptimal
Wide39% 61.0%±2.5 n=998 54% ▲
Body11% 58.1%±4.6 n=283 0% ▼
T50% 60.5%±2.2 n=1,256 46% ▼

Consistent with an optimal mix (p = 0.57).
Optimal mix: +0.7 per 100 first serves.

Exploitability 0.68 points per 100 first serves What the optimal mix would win over the current one, both courts. More exploitable than 100% of WTA servers. Tested on matches they weren't fitted on, WTA mixes picked this way win 0.42 per 100 first serves on average.

Repeating the previous direction to the same court: −1.0±2.2 points per 100 against switching. Negative means returners read repeats. Tour-wide, repeating costs women about 0.4 points per 100 and costs men nothing, so men's returners don't measurably anticipate direction. (1,851 repeats, 3,316 switches.)

Return by serve direction

Return points won against each serve direction, compared with the tour average.

ServeCourtDirectionPointsWonvs tour
1stAd courtBody 378 44% −0.2±4.0
1stAd courtT 584 32% −3.7±3.1
1stAd courtWide 635 32% −2.8±3.0
1stDeuce courtBody 435 42% −0.5±3.8
1stDeuce courtT 567 28% −4.6±3.0
1stDeuce courtWide 729 30% −4.5±2.7
2ndAd courtBody 428 55% −0.1±3.8
2ndAd courtT 160 57% +1.5±5.9
2ndAd courtWide 370 54% +0.7±4.1
2ndDeuce courtBody 501 55% +0.4±3.6
2ndDeuce courtT 280 55% −0.9±4.6
2ndDeuce courtWide 274 53% −0.8±4.7

Signature patterns

Recurring sequences that win more than Naomi Osaka's own baseline, ranked by edge weighted by how often they're used.

Serve → +1

  1. Wide serve (deuce court) → FH crosscourt used 2.2% · won 61% · −3.7±6.9 vs own baseline
  2. Wide serve (deuce court) → BH crosscourt used 2.1% · won 60% · −4.6±7.0 vs own baseline
  3. T serve (deuce court) → FH crosscourt used 2.1% · won 58% · −6.0±7.1 vs own baseline
  4. Wide serve (deuce court) → FH down the line used 2.7% · won 58% · −6.6±6.4 vs own baseline
  5. Body serve (deuce court) → BH crosscourt used 2.4% · won 55% · −9.0±6.8 vs own baseline

Return

  1. vs wide serve (ad court) → BH crosscourt, mid used 4.4% · won 58% · +16.9±5.3 vs own baseline
  2. vs body serve (deuce court) → BH through the middle, deep used 2.2% · won 55% · +13.6±7.2 vs own baseline
  3. vs body serve (deuce court) → BH through the middle, mid used 3.1% · won 51% · +10.0±6.3 vs own baseline
  4. vs wide serve (ad court) → BH through the middle, deep used 2.1% · won 53% · +11.8±7.4 vs own baseline
  5. vs T serve (deuce court) → BH through the middle, deep used 2.4% · won 52% · +10.7±7.0 vs own baseline

Rally, consecutive own shots

  1. FH crosscourt → FH down the line used 4.3% · won 58% · +8.1±5.7 vs own baseline
  2. FH crosscourt → BH crosscourt used 4.8% · won 56% · +6.2±5.5 vs own baseline
  3. FH down the line → FH crosscourt used 2.4% · won 57% · +7.4±7.3 vs own baseline
  4. FH through the middle → FH crosscourt used 3.1% · won 56% · +6.4±6.6 vs own baseline
  5. BH down the line → FH down the line used 2.1% · won 56% · +6.7±7.7 vs own baseline

Discovered sequences

Mined from every me → opponent → me run of three shots, with no templates. Ranked by how much more often Naomi Osaka wins the point once the sequence happens, weighted by how often it happens. Think of them as chess openings.

  1. BH crosscourt → BH through the middle → FH crosscourt used 0.9% · won 58% · +9.2±7.2 vs own baseline · +6.3 vs tour on the same sequence Disrupted by Iga Swiatek (3/7), Donna Vekic (4/8)
  2. FH crosscourt → FH crosscourt → FH down the line used 0.8% · won 57% · +8.5±7.4 vs own baseline · +11.9 vs tour on the same sequence Disrupted by Serena Williams (3/6), Elina Svitolina (5/6)
  3. BH crosscourt return, mid → BH crosscourt → BH crosscourt used 0.4% · won 61% · +12.7±9.8 vs own baseline · +20.1 vs tour on the same sequence Disrupted by Jennifer Brady (7/8)
  4. FH crosscourt → FH through the middle → BH crosscourt used 0.7% · won 58% · +8.8±7.8 vs own baseline · +7.8 vs tour on the same sequence Disrupted by Karolina Muchova (4/6), Victoria Azarenka (4/6)
  5. FH crosscourt → FH through the middle → FH crosscourt used 0.7% · won 57% · +7.7±8.0 vs own baseline · +3.7 vs tour on the same sequence Disrupted by Sara Sorribes Tormo (3/7), Elina Svitolina (3/6)
  6. BH crosscourt → BH through the middle → FH down the line used 0.7% · won 56% · +7.2±8.0 vs own baseline · +4.9 vs tour on the same sequence

Strengths and vulnerabilities

Value per 100 shots compared with the average player hitting (strengths) or facing (vulnerabilities) the same shot. Only shot types seen at least 120 times.

Hurts opponents most with

Body 2nd serve · deuce court+2.9593
Wide 2nd serve · ad court+2.6306
T 2nd serve · ad court+2.3252
Wide 2nd serve · deuce court+1.7237
Wide 1st serve · deuce court+1.71,216

Most exposed to

FH to their forehand · serve +1−2.8536
BH to the middle · serve +1−1.8595
T 2nd serve · deuce court−1.5277
FH to their backhand · serve +1−1.4608
FH to their forehand · return +1−1.3392

Best-equipped opponents

Active players whose shot mix lines up best against these weaknesses, by structural compatibility per 100 rally shots: Sara Sorribes Tormo +2.70, Caroline Wozniacki +2.40, Daria Kasatkina +1.82, Angelique Kerber +1.82, Sara Errani +1.72

Favourable matchups

Sara Errani +1.20, Angelique Kerber +0.57, Marie Bouzkova +0.54, Elina Avanesyan +0.46, Katie Volynets +0.24

Active players who are best at the shot in the top weakness: Barbora Krejcikova, Shelby Rogers, Sara Sorribes Tormo, Jil Teichmann, Maria Sakkari

Tactical fingerprint

Each bar shows how far a style trait is from the WTA average, in standard deviations.

Point-ending shots30.5%
T serves · ad50%
Unforced errors / shot13.4%
BH down the line25%
T serves · deuce43%
Wide serves · deuce44%
Deep returns33%
FH down the line29%
Serve & volley0%
Wide serves · ad39%
Run-around forehands5%
Chipped returns4%
Through the middle25%
Backhand slice4%
Points at net4%
1st serve in59%
Drop shots / shot0.5%
Forehand share50%
Avg rally length3.5

Plays most like

  1. Serena Williams 1998–2026 plan v
  2. Veronika Kudermetova 2018–2025 plan v
  3. Ekaterina Alexandrova 2017–2026 plan v
  4. Karolina Pliskova 2013–2026 plan v
  5. Elena Gabriela Ruse 2016–2026 plan v
  6. Lindsay Davenport 1995–2006 plan v
  7. Maria Sharapova 2003–2020 plan v
  8. Anett Kontaveit 2015–2023 plan v

Closest from another era

  1. Lindsay Davenport 1995–2006
  2. Jelena Dokic 2000–2009
  3. Anastasia Myskina 2002–2006

Charted matches